Numerically exact configuration interaction at quadrillion-determinant scale
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| Vydáno v: | Nature Communications vol. 16, no. 1 (2025), p. 11016-11028 |
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| 045 | 2 | |b d20250101 |b d20251231 | |
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| 100 | 1 | |a Shayit, Agam |u Department of Physics, University of Washington, Seattle, WA, USA (ROR: https://ror.org/00cvxb145) (GRID: grid.34477.33) (ISNI: 0000 0001 2298 6657) | |
| 245 | 1 | |a Numerically exact configuration interaction at quadrillion-determinant scale | |
| 260 | |b Nature Publishing Group |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a The combinatorial growth of configuration interaction (CI) has long limited this formally exact quantum chemistry method to only the smallest molecules. Here, we report a numerically exact CI calculation exceeding one quadrillion (1015) determinants, made possible by a lossless categorical compression strategy within the small-tensor-product distributed active space (STP-DAS) framework. This approach overcomes the traditional memory bottlenecks of CI by a numerically exact compression of the wavefunction representation and reformulating the most computationally demanding matrix–vector operations. Using this method, we performed a fully relativistic CI calculation of the ground state of HBrTe with over 1015 complex-valued determinants in just 34.5 h on 1000 computing nodes—the largest CI calculation ever reported. We further achieved fast computation for systems with hundreds of billions of determinants on only a few compute nodes. Extensive benchmarks confirm that the method retains full numerical exactness while cutting memory and computational cost by orders of magnitude. Compared to previous state-of-the-art CI calculations, this work achieves a 1000 times increase in CI space, a 106-fold increase in floating-point operations performed, and a 106-fold improvement in computational speed.Due to the combinatorial scaling of configuration interaction methods, formally exact quantum chemistry results are only available for small systems. Here, the authors present an implementation using categorical compression, enabling efficient modeling of many electron systems. | |
| 653 | |a Benchmarks | ||
| 653 | |a Computer memory | ||
| 653 | |a Computer peripherals | ||
| 653 | |a Combinatorial analysis | ||
| 653 | |a Hilbert space | ||
| 653 | |a Configuration interaction | ||
| 653 | |a Quantum chemistry | ||
| 653 | |a Tensors | ||
| 653 | |a Nodes | ||
| 653 | |a Decomposition | ||
| 653 | |a Computing costs | ||
| 653 | |a Computer applications | ||
| 653 | |a Algorithms | ||
| 653 | |a Compression | ||
| 653 | |a Determinants | ||
| 653 | |a Floating point arithmetic | ||
| 653 | |a Wave functions | ||
| 653 | |a Environmental | ||
| 700 | 1 | |a Liao, Can |u Department of Chemistry, University of Washington, Seattle, WA, USA (ROR: https://ror.org/00cvxb145) (GRID: grid.34477.33) (ISNI: 0000 0001 2298 6657) | |
| 700 | 1 | |a Upadhyay, Shiv |u Department of Chemistry, University of Washington, Seattle, WA, USA (ROR: https://ror.org/00cvxb145) (GRID: grid.34477.33) (ISNI: 0000 0001 2298 6657) | |
| 700 | 1 | |a Hu, Hang |u Molecular Engineering and Sciences Institute, University of Washington, Seattle, WA, USA (ROR: https://ror.org/00cvxb145) (GRID: grid.34477.33) (ISNI: 0000 0001 2298 6657) | |
| 700 | 1 | |a Zhang, Tianyuan |u Department of Chemistry, University of Washington, Seattle, WA, USA (ROR: https://ror.org/00cvxb145) (GRID: grid.34477.33) (ISNI: 0000 0001 2298 6657) | |
| 700 | 1 | |a DePrince III, A. Eugene |u Department of Chemistry and Biochemistry, Florida State University, Tallahassee, FL, USA (ROR: https://ror.org/05g3dte14) (GRID: grid.255986.5) (ISNI: 0000 0004 0472 0419) | |
| 700 | 1 | |a Yang, Chao |u Applied Mathematics and Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA (ROR: https://ror.org/02jbv0t02) (GRID: grid.184769.5) (ISNI: 0000 0001 2231 4551) | |
| 700 | 1 | |a Li, Xiaosong |u Department of Chemistry, University of Washington, Seattle, WA, USA (ROR: https://ror.org/00cvxb145) (GRID: grid.34477.33) (ISNI: 0000 0001 2298 6657) | |
| 773 | 0 | |t Nature Communications |g vol. 16, no. 1 (2025), p. 11016-11028 | |
| 786 | 0 | |d ProQuest |t Health & Medical Collection | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3281495096/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3281495096/fulltext/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3281495096/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |